Engineering Papers⌕ Search

SEARCH · Engineering Papers

Results for “Sensitivity analysis”

Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 1,495 records · Page 83
All sourcesNASA NTRSDOE OSTI
DOE OSTI2018

A Kinetic Model for Modification of MgAl{sub 2}O{sub 4} Spinel Inclusions During Calcium Treatment in the Ladle Furnace

A common approach in the processing of Al-killed steels is the modification of alumina inclusions by calcium treatment. A model for this process has already been developed by the current authors and validated by means of plant data. Often, magnesium aluminate spinels are also present and transformed to magnesium calcium aluminate inclusions during calcium treatment. In the current study, a fundamental kinetic model is proposed for modification of spinel inclusions considering mass transfer of solute through the boundary layer to the inclusion and diffusion within the product layer. Sensitivity analysis has been carried out to determine rate-controlling step for spinel modification. The rate of transformation of spinel inclusions is compared with alumina inclusions reported in the current authors’ prior model.

36 MATERIALS SCIENCE↗
DOE OSTI2016

Neuroplastic Response After Radiation Therapy for Pediatric Brain Tumors: A Pilot Study

Purpose: Clinically effective measurement of cognitive toxicity from photon radiation therapy (XRT) should be accurate, sensitive, and specific. This pilot study tested translational findings on phasic changes in children's memory systems that are sensitive and insensitive to toxic XRT effects to identify a possible neuroplastic effect. Methods and Materials: Memory processes were prospectively tested before XRT and at 3 later time points up to 2 years in 35 children with mixed primary brain tumors who had not experienced recurrence. Memory processes were verbal-semantic, visual-semantic, and visual-perceptual, including accuracy, speed to recall, encoding, retrieval, and recognition. The mixed-effects model included time (to estimate slope), covariates (age, tumor locus, XRT field, and medications) as fixed effects, and individual random intercepts. A sensitivity analysis examined the influence of XRT dose to the hippocampi on memory. Results: Retrieval from long-term verbal-semantic memory declined 2 months after completing XRT, as seen in adults, and was lowest at 1 year, which was delayed in comparison with adults. Double dissociation from visual-perceptual memory at baseline and 2 months was found, consistent with adults. Recovery was demonstrated 2 years after XRT. Patterns were unchanged when dose to hippocampus was included in the model. Conclusions: Verbal and semantic long-term retrieval is specifically sensitive to XRT-related cognitive dysfunction, without effect on visual-perceptual memory. Children reached nadir in XRT-sensitive memory 1 year after XRT and recovered by 2 years, which is later than that observed in adults. The protracted period of post-XRT injury may represent the maturation of the human hippocampus and white matter into late adolescence.

62 RADIOLOGY AND NUCLEAR MEDICINE↗
DOE OSTI2022

Tritium Transport Modeling at the Pore Scale in Ceramic Breeder Materials Using TMAP8

Fusion reactors depend on the blanket material to breed and release tritium at the same rate or faster than it is consumed by the fusion reaction. Cellular ceramic breeders (CCBs) are dense materials that can maintain a high tritium breeding ratio while promoting tritium release because of highly connected pores. Assessing the tritium breeding capabilities of these materials requires a combination of extensive experimental and modeling efforts. In this work, we develop and calibrate a multiphysics model of tritium transport. This novel model accounts for ceramic and pore diffusion, trapping and detrapping, and several surface reactions at the pore surface. We perform a sensitivity analysis and calibrate the model by comparing its predictions against experimental measurements of deuterium absorption. The calibrated model is then used to model tritium absorption in samples with different pore microstructures to investigate the effect of pore interconnectivity on tritium absorption. The model is part of the development of the multiscale, multiphysics framework for tritium transport [i.e., the Tritium Migration Analysis Program (TMAP8)], which is itself built on top of the finite-element multiphysics framework multiphysics object-oriented simulation environment (MOOSE). This study demonstrates some of TMAP8’s capabilities and is the first step toward assessing the tritium breeding capabilities of ceramic breeder material designs.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2019

Development of Waste Inventory for Probabilistic Performance Assessment Modeling - 19361

Estimation of radioactive waste inventory is a key initial step in the development of an environmental fate and transport model for performance assessment (PA) of radioactive waste sites. PA model output is often sensitive to parameters that represent inventory as a source term, yet estimation is a difficult problem. Inventory estimation for a probabilistic performance assessment (PPA) is related to, but distinct from, that performed for waste excavation, characterization, and offsite disposal. The latter appropriately focuses on obtaining the most detailed information possible on specific hazards and locations; however, these questions cannot be fully answered without intrusive site characterization efforts. This type of characterization is often not feasible when assembling information regarding a source term in a PPA model. Development of waste inventory for a PPA is one piece of a larger hierarchical model. The physical process model represented by Goldsim computer code represents one level of the hierarchy, and the second level of the hierarchy involves estimation of inputs such as inventory, transport, and risk parameters. The estimation of inputs is not a straightforward problem. The parameters of a computer model often do not have an equivalence to the physical quantities they describe, and estimation of the physical quantities themselves can be difficult due to limitations of available information. Inventory information for the West Valley Site in upstate New York is based on data from historical shipping and disposal forms. In the 1990's, the West Valley Demonstration Project (WVDP) compiled information from existing databases and historical waste records into one complete modern database. A conceptual model was then applied and used with recorded information to characterize the waste mass and radionuclide composition for each waste burial. Information was ultimately aggregated over all waste records to estimate the mass of each radionuclide within each trench, hole, or caisson. Three decades later, we revisit the master database, make updates with newly-identified information, and incorporate the conceptual model previously used for inventory estimation in the hierarchical modeling framework. We characterize uncertainty using probability distributions for waste mass and radionuclide composition at the individual shipment or individual burial level. Uncertainty incorporated at the lowest level of the hierarchy is ultimately carried through to uncertainty in PPA model endpoints. Sensitivity analysis of early model results is then applied to identify influential inputs and guide subsequent efforts towards parameters that drive risk. (authors)

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2012

Improving Air-Conditioner and Heat Pump Modeling (Presentation made at the Building America Stakeholders Meeting) [Slides]

A new approach to modeling residential air conditioners and heat pumps allows users to model systems by specifying only the more readily-available SEER/EER/HSPF-type metrics. Manufacturer data was used to generate full sets of model inputs for over 450 heat pumps and air conditioners. A sensitivity analysis identified which inputs can be safely defaulted 'behind-the-scenes' without negatively impacting the reliability of energy simulations.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2016

NORM Concentration Determination in Common Materials in an Urban Environment

The United States government performs searches for illicit radiation sources before and during large special events, such as State of the Union addresses, presidential inaugurations, or the recent papal visit. Clear detection of sources is difficult due to natural background radiation, which can vary greatly throughout a given search area. Background radiation is mostly a function of the materials used in roadways, sidewalks, and building exteriors. A team of scientists from Oak Ridge National Laboratory (ORNL), Lawrence Livermore National Laboratory (LLNL), the Remote Sensing Laboratory (RSL), and Lawrence Berkeley National Laboratory (LBNL) is exploring the nature and variability of background count rates in order to improve the performance of searches in urban areas. A series of background measurements have been and will continue to be taken at a Military Operations on Urban Terrain (MOUT) environment at the Fort Indiantown Gap (FTIG) National Guard training facility in Pennsylvania. This site replicates a small town with asphalt roads, concrete intersections, buildings, sidewalks, curbs, and gravel parking areas. Unlike an actual urban area, traffic and pedestrian access can be easily controlled to avoid interference with measurements. This paper documents the efforts focused on characterizing the various concentrations of radioactive material found in these materials at the site. The NORM concentrations determined from this work will be incorporated in to a large-scale simulation (a 'virtual test-bed') that can be used to investigate various search techniques and algorithms, detector suite configurations, and to produce representative synthetic data for future work. A combination of measurement and simulation was used to determine the concentration of {sup 40}K and the radioactive nuclides in the uranium series and the thorium series in several materials at the FTIG MOUT site. The predicted concentrations are consistent with other published results, and they matched favorably with synthetic data generated with MCNP6 models using the determined NORM concentrations and estimates of the FTIG environment as described by available construction plans and using standard material assumptions. Future measurements will incorporate lessons learned from this study. More measurements will be made of the concrete intersections at the site. The methodology explained in this report will also be carried out on building materials in an effort to characterize NORM concentrations in these background sources. Other modeling and simulation work that should be conducted includes a robust sensitivity analysis in which the effects of small changes to the model (and measurement) system can be characterized to help bound the uncertainty on the final NORM concentration predictions. (authors)

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2013

Coordinated activities on evaluation of collisional data for fusion applications

It is the role of the Atomic and Molecular Data Unit of the International Atomic Energy Agency to review progress in the production, compilation and evaluation of atomic, molecular and plasma-surface interaction (AM/PSI) data for the fusion program and to support the development of internationally recommended libraries of AM/PSI data for fusion. In response to increasing requests from the fusion community the Unit has increased its effort to promote the assessment of data quality by organizing a series of meetings on the relevant issues: 1) Error propagation and sensitivity analysis, 2) Current status of evaluated databases, 3) Uncertainty estimates of theoretical data, 4) Experimental data evaluation, 5) Data evaluation methods and semi-empirical fits and 6) Establishment of an evaluators' network. The discussions and conclusions are summarized here.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2020

10° off-axis testing of CFRP using DIC: A study on strength, strain and modulus

For the determination of the shear properties such as strength, strain and modulus of unidirectionally reinforced composites, nearly a dozen measurement techniques exist, several of which have found their way into standards. One non-standardized method for sheet materials is the 10° off-axis tensile test of unidirectional coupons. The current work focuses on the experimental investigation of tensile testing of CFRP-UD coupon specimens using the 10° off-axis test and DIC strain mapping to measure the full-field deformation response. A sensitivity analysis on the measured stresses, strains and moduli is performed by varying the aspect ratio of the specimens and the location of strain measurement. Test related uncertainties such as the loading angle and specimen preparation details are investigated and quantified with the help of these full-field DIC measurements.

42 ENGINEERING↗
DOE OSTI2012

Uncertainty Quantification of Calculated Temperatures for the AGR-1 Experiment

This report documents an effort to quantify the uncertainty of the calculated temperature data for the first Advanced Gas Reactor (AGR-1) fuel irradiation experiment conducted in the INL's Advanced Test Reactor (ATR) in support of the Next Generation Nuclear Plant (NGNP) R&D program. Recognizing uncertainties inherent in physics and thermal simulations of the AGR-1 test, the results of the numerical simulations can be used in combination with the statistical analysis methods to improve qualification of measured data. Additionally, the temperature simulation data for AGR tests can be used for validation of the fuel transport and fuel performance simulation models. The crucial roles of the calculated fuel temperatures in ensuring achievement of the AGR experimental program objectives require accurate determination of the model temperature uncertainties. The report is organized into three chapters. Chapter 1 introduces the AGR Fuel Development and Qualification program and provides overviews of AGR-1 measured data, AGR-1 test configuration and test procedure, and thermal simulation. Chapters 2 describes the uncertainty quantification procedure for temperature simulation data of the AGR-1 experiment, namely, (i) identify and quantify uncertainty sources; (ii) perform sensitivity analysis for several thermal test conditions; (iii) use uncertainty propagation to quantify overall response temperature uncertainty. A set of issues associated with modeling uncertainties resulting from the expert assessments are identified. This also includes the experimental design to estimate the main effects and interactions of the important thermal model parameters. Chapter 3 presents the overall uncertainty results for the six AGR-1 capsules. This includes uncertainties for the daily volume-average and peak fuel temperatures, daily average temperatures at TC locations, and time-average volume-average and time-average peak fuel temperatures.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2020

Multi‐hypothesis comparison of Farquhar and Collatz photosynthesis models reveals the unexpected influence of empirical assumptions at leaf and global scales

Abstract Mechanistic photosynthesis models are at the heart of terrestrial biosphere models (TBMs) simulating the daily, monthly, annual and decadal rhythms of carbon assimilation ( A ). These models are founded on robust mathematical hypotheses that describe how A responds to changes in light and atmospheric CO 2 concentration. Two predominant photosynthesis models are in common usage: Farquhar (FvCB) and Collatz (CBGB). However, a detailed quantitative comparison of these two models has never been undertaken. In this study, we unify the FvCB and CBGB models to a common parameter set and use novel multi‐hypothesis methods (that account for both hypothesis and parameter variability) for process‐level sensitivity analysis. These models represent three key biological processes: carboxylation, electron transport, triose phosphate use (TPU) and an additional model process: limiting‐rate selection. Each of the four processes comprises 1–3 alternative hypotheses giving 12 possible individual models with a total of 14 parameters. To broaden inference, TBM simulations were run and novel, high‐resolution photosynthesis measurements were made. We show that parameters associated with carboxylation are the most influential parameters but also reveal the surprising and marked dominance of the limiting‐rate selection process (accounting for 57% of the variation in A vs. 22% for carboxylation). The limiting‐rate selection assumption proposed by CBGB smooths the transition between limiting rates and always reduces A below the minimum of all potentially limiting rates, by up to 25%, effectively imposing a fourth limitation on A . Evaluation of the CBGB smoothing function in three TBMs demonstrated a reduction in global A by 4%–10%, equivalent to 50%–160% of current annual fossil fuel emissions. This analysis reveals a surprising and previously unquantified influence of a process that has been integral to many TBMs for decades, highlighting the value of multi‐hypothesis methods.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2024

A Bayesian Multi-fidelity Neural Network to Predict Nonlinear Frequency Backbone Curves

The use of structural mechanics models during the design process often leads to the development of models of varying fidelity. Often low-fidelity models are efficient to simulate but lack accuracy, while the high-fidelity counterparts are accurate with less efficiency. Here, this paper presents a multi-fidelity surrogate modeling approach that combines the accuracy of a high-fidelity finite element model with the efficiency of a low-fidelity model to train an even faster surrogate model that parameterizes the design space of interest. The objective of these models is to predict the nonlinear frequency backbone curves of the Tribomechadynamics Research Challenge benchmark structure which exhibits simultaneous nonlinearities from frictional contact and geometric nonlinearity. The surrogate model consists of an ensemble of neural networks that learn the mapping between low and high-fidelity data through nonlinear transformations. Bayesian neural networks are used to assess the surrogate model's uncertainty. Once trained, the multi-fidelity neural network is used to perform sensitivity analysis to assess the influence of the design parameters on the predicted backbone curves. Additionally, Bayesian calibration is performed to update the input parameter distributions to correlate the model parameters to the collection of experimentally measured backbone curves.

42 ENGINEERING↗
DOE OSTI2012

Simulation of 1% hot leg SBLOCA with TRACE5

During a Small Break Loss-of-Coolant Accident (SBLOCA) transient, depressurization can be slow enough to delay the Accumulators (ACC) entry for a long time. Actuation of High Pressure Injection (HPI) system is then necessary in order to maintain the core temperature low enough to avoid core boil off, and consequently avoiding the core level to fall below fuel rods level, thus producing a temperature trip in the fuel cladding. In this frame, the OECD/NEA ROSA Project Test 1.2 (SB-HL-17 in Japan Atomic Energy Agency (JAEA)) has been simulated using the thermal-hydraulic code TRACES. Test 1.2 was performed in the Large Scale Test Facility (LSTF) reproducing a 1% hot leg SBLOCA in a Pressurized Water Reactor (PWR). A comparison between experimental and the main simulated variables was performed to study the effect of important parameters (liquid stratification, geometry and size) to model the break. Finally, in an Emergency Core Cooling System (ECCS) failure scenario, loss of coolant is large enough to produce core boil-off and a Peak Cladding Temperature (PCT) excursion. With this purpose a sensitivity analysis varying the HPI mass flow rate has been performed covering the range between HPI actuation and failure. (authors)

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗
DOE OSTI2017

FY17 Status Report on NEAMS Neutronics Activities

Under the U.S. DOE NEAMS program, the high-fidelity neutronics code system has been developed to support the multiphysics modeling and simulation capability named SHARP. The neutronics code system includes the high-fidelity neutronics code PROTEUS, the cross section library and preprocessing tools, the multigroup cross section generation code MC2-3, the in-house meshing generation tool, the perturbation and sensitivity analysis code PERSENT, and post-processing tools. The main objectives of the NEAMS neutronics activities in FY17 are to continue development of an advanced nodal solver in PROTEUS for use in nuclear reactor design and analysis projects, implement a simplified sub-channel based thermal-hydraulic (T/H) capability into PROTEUS to efficiently compute the thermal feedback, improve the performance of PROTEUS-MOCEX using numerical acceleration and code optimization, improve the cross section generation tools including MC2-3, and continue to perform verification and validation tests for PROTEUS.

47 OTHER INSTRUMENTATION↗
DOE OSTI2012

The Timing of Salvage Radiotherapy After Radical Prostatectomy: A Systematic Review

Purpose: Salvage radiotherapy (SRT) after radical prostatectomy can potentially eradicate residual microscopic disease. Defining the optimal patient and treatment factors is essential and is particularly relevant within the context of adjuvant vs early vs delayed postoperative radiotherapy (RT). Methods and Materials: A systematic review of all published SRT studies was performed to identify the pathologic, clinical, and treatment factors associated with relapse-free survival (RFS) after SRT. A total of 41 studies encompassing 5597 patients satisfied the study entry criteria. Radiobiologic interpretation of biochemical tumor control was used to provide the framework for the observed relationships. Results: Prostate-specific antigen (PSA) level before SRT (P<.0001) and RT dose (P=.0052) had a significant and independent association with RFS. There was an average 2.6% loss of RFS for each incremental 0.1 ng/mL PSA at the time of SRT (95% CI, {approx}2.2-3.1). With a PSA level of 0.2 ng/mL or less before SRT, the RFS approached 64%. The dose for salvage RT in the range of 60-70 Gy seemed to be on the steep part of the sigmoidal dose-response curve, with a dose of 70 Gy achieving 54% RFS compared with only 34% for 60 Gy. There was a 2% improvement in RFS for each additional Gy (95% CI, {approx}0.9-3.2). The observed dose-response was less robust on sensitivity analysis. Conclusions: This study provides Level 2a evidence for initiating SRT at the lowest possible PSA. Dose escalation is also suggested by the data. Progressively better tumor control rates with SRT after radical prostatectomy are achieved with a lower PSA at initiation and with a higher RT dose. Early salvage RT may be an equivalent strategy to adjuvant RT.

62 RADIOLOGY AND NUCLEAR MEDICINE↗
DOE OSTI2015

Noise analysis of genome-scale protein synthesis using a discrete computational model of translation

Noise in genetic networks has been the subject of extensive experimental and computational studies. However, very few of these studies have considered noise properties using mechanistic models that account for the discrete movement of ribosomes and RNA polymerases along their corresponding templates (messenger RNA (mRNA) and DNA). The large size of these systems, which scales with the number of genes, mRNA copies, codons per mRNA, and ribosomes, is responsible for some of the challenges. Additionally, one should be able to describe the dynamics of ribosome exchange between the free ribosome pool and those bound to mRNAs, as well as how mRNA species compete for ribosomes. We developed an efficient algorithm for stochastic simulations that addresses these issues and used it to study the contribution and trade-offs of noise to translation properties (rates, time delays, and rate-limiting steps). The algorithm scales linearly with the number of mRNA copies, which allowed us to study the importance of genome-scale competition between mRNAs for the same ribosomes. We determined that noise is minimized under conditions maximizing the specific synthesis rate. Moreover, sensitivity analysis of the stochastic system revealed the importance of the elongation rate in the resultant noise, whereas the translation initiation rate constant was more closely related to the average protein synthesis rate. We observed significant differences between our results and the noise properties of the most commonly used translation models. Overall, our studies demonstrate that the use of full mechanistic models is essential for the study of noise in translation and transcription.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2016

Probabilistic Assessment of Above Zone Pressure Predictions at a Geologic Carbon Storage Site

Carbon dioxide (CO2) storage into geological formations is regarded as an important mitigation strategy for anthropogenic CO2 emissions to the atmosphere. This study first simulates the leakage of CO2 and brine from a storage reservoir through the caprock. Then, we estimate the resulting pressure changes at the zone overlying the caprock also known as Above Zone Monitoring Interval (AZMI). A data-driven approach of arbitrary Polynomial Chaos (aPC) Expansion is then used to quantify the uncertainty in the above zone pressure prediction based on the uncertainties in different geologic parameters. Finally, a global sensitivity analysis is performed with Sobol indices based on the aPC technique to determine the relative importance of different parameters on pressure prediction. The results indicate that there can be uncertainty in pressure prediction locally around the leakage zones. The degree of such uncertainty in prediction depends on the quality of site specific information available for analysis. The scientific results from this study provide substantial insight that there is a need for site-specific data for efficient predictions of risks associated with storage activities. The presented approach can provide a basis of optimized pressure based monitoring network design at carbon storage sites.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2022

TRITIUM TRANSPORT MODELING AT THE PORE SCALE IN CERAMIC BEEDER MATERIALS USING TMAP8

Fusion reactors depend on the blanket material to breed and release tritium at the same rate or faster than it is consumed by the fusion reaction. Cellular ceramic breeders are dense materials that can maintain a high tritium breeding ratio while promoting tritium release thanks to highly connected pores. Assessing the tritium breeding capabilities of these materials requires a combination of extensive experimental and modeling efforts. In this work, we develop and calibrate a multiphysics model of tritium transport. This novel model accounts for ceramic and pore diffusion, trapping and detrapping, and several surface reactions at the pore surface. We perform a sensitivity analysis and calibrate the model by comparing its predictions against experimental measurements of deuterium absorption. The calibrated model is then used to model tritium absorption in samples with different pore microstructures to investigate the effect of pore interconnectivity on tritium absorption. The model is part of the development of the multiscale, multiphysics framework for tritium transport (i.e., the Tritium Migration Analysis Program [TMAP8]), which is itself built on top of the finite element multiphysics framework MOOSE. This study demonstrates some of TMAP8’s capabilities, and is the first step toward assessing the tritium breeding capabilities of ceramic breeder material designs.

08 HYDROGEN↗